1 files changed, 58 insertions, 0 deletions
diff --git a/contrib/lua-torch/nn/VolumetricReplicationPadding.lua b/contrib/lua-torch/nn/VolumetricReplicationPadding.lua
new file mode 100644
index 000000000..31a9503fd
--- /dev/null
+++ b/contrib/lua-torch/nn/VolumetricReplicationPadding.lua
@@ -0,0 +1,58 @@
+local VolumetricReplicationPadding, parent =
+   torch.class('nn.VolumetricReplicationPadding', 'nn.Module')
+
+function VolumetricReplicationPadding:__init(pleft, pright, ptop, pbottom,
+                                             pfront, pback)
+   parent.__init(self)
+   self.pleft = pleft
+   self.pright = pright or self.pleft
+   self.ptop = ptop or self.pleft
+   self.pbottom = pbottom or self.pleft
+   self.pfront = pfront or self.pleft
+   self.pback = pback or self.pleft
+end
+
+function VolumetricReplicationPadding:updateOutput(input)
+   if input:dim() == 4 or input:dim() == 5 then
+      input.THNN.VolumetricReplicationPadding_updateOutput(
+         input:cdata(), self.output:cdata(),
+         self.pleft, self.pright, self.ptop, self.pbottom, self.pfront,
+         self.pback)
+   else
+      error('input must be 4 or 5-dimensional')
+   end
+   return self.output
+end
+
+function VolumetricReplicationPadding:updateGradInput(input, gradOutput)
+   if input:dim() == 4 and gradOutput:dim() == 4 then
+      assert(input:size(1) == gradOutput:size(1)
+             and input:size(2) + self.pfront + self.pback == gradOutput:size(2)
+             and input:size(3) + self.ptop + self.pbottom == gradOutput:size(3)
+             and input:size(4) + self.pleft + self.pright == gradOutput:size(4),
+             'input and gradOutput must be compatible in size')
+   elseif input:dim() == 5 and gradOutput:dim() == 5 then
+      assert(input:size(1) == gradOutput:size(1)
+             and input:size(2) == gradOutput:size(2)
+             and input:size(3) + self.pfront + self.pback == gradOutput:size(3)
+             and input:size(4) + self.ptop + self.pbottom == gradOutput:size(4)
+             and input:size(5) + self.pleft + self.pright == gradOutput:size(5),
+             'input and gradOutput must be compatible in size')
+   else
+      error(
+         [[input and gradOutput must be 4 or 5-dimensional
+         and have equal number of dimensions]]
+         )
+   end
+   input.THNN.VolumetricReplicationPadding_updateGradInput(
+      input:cdata(), gradOutput:cdata(), self.gradInput:cdata(),
+      self.pleft, self.pright, self.ptop, self.pbottom, self.pfront, self.pback)
+   return self.gradInput
+end
+
+function VolumetricReplicationPadding:__tostring__()
+   return torch.type(self) ..
+   string.format('(left=%d, right=%d, top=%d, bottom=%d, front=%d, back=%d)',
+                 self.pleft, self.pright, self.ptop, self.pbottom,
+                 self.pfront, self.pback)
+end